Thinking Really Big About Data: UPMC’s Lisa Khorey Talks About What’s Behind the Organization’s Groundbreaking Five-Year Initiative

In the end, it will simplify things, and things that are simple are efficient. And that’s the information management challenge, right? To simplify and harmonize. But to get to simple, you have to wade through a whole lot of complex; and that’s the biggest challenge of the program. We did spend some time looking at what had gone on before this in other organizations and other industries, and what incents people and brings value. And what’s worth even doing? Not everything that can be counted should be measured. But the most challenging part really is the “soft” things: how do you keep the executive team engaged? How do you keep the stamina of the program engaged? How do you think globally but act locally? And the most challenging part really is the blocking and tackling.

What kinds of internal teams will be involved in this initiative?

We tried not to matrix it too much. We really put together two teams. And we thought, how do we create a path between the nurse all the way up to the top of the organization? It’s a transformation project; and a whole operational structure was defined, and it follows the organization, meaning that the Institute for Personalized Medicine is the key nexus team between the University of Pittsburgh and UPMC; and there’s a provider division person, a payer division person, a finance person; so there’s a whole team of people at that second level who are empowered. And then there’s a whole set of workgroups involved, a spider web of workgroups. There will probably 20 different workgroups involved altogether. Our intention was not to govern through a bureaucracy, but actually to enable decisions to be made.

Executing across an organization as big and complex as yours is always challenging.

It is, but it’s our very size and complexity that led to this realization, that no single part of the organization could solve these problems by itself. We have lots and lots of analytics—data warehouses, business intelligence, all kinds of stuff—but they always hit a limit. There’s always some piece of data that’s missing. So if you really want to understand science and variations in patients and patient care and to find all those inefficiencies across the entire organization, then you have to look at the whole data set.

Will you be over the whole program?

I only serve in a role over the technology part of it; Dr. Steve Schapiro will be over the entirety of it.

What should our readership think about this, and do?

What we really needed to do was to stop focusing on what we would do in the next six months, and really set a north star on what we hoped to achieve in the next five years or so. We had already been deploying EHRs since 1999; and we wanted to set our focus on things a little bigger and a little further out, so that we could determine what we did not need to do. The thing is that if you just make a list, everything is really priority one, and it really paralyzes you. So focus on your north star; and then derive efficiencies from that. A lot of what we’re doing here was already here; but we just had to be a bit more inclusive. And finally, I’ve learned that everybody does not change on day one; the value will come.